import cv2
import matplotlib.pyplot as plt

img = cv2.imread('birds.jpg')

resize_img = cv2.resize(img, new_size)
resize_img = cv2.resize(img,(0, 0),fx=0.5, fy=0.7, interpolation = cv2.INTER_AREA)

plt.imshow(resize_img)

import cv2
import matplotlib.pyplot as plt

img = cv2.imread('birds.jpg')
h, w, c = img.shape

# Different scaling ratios
scaling_ratio = [0.1, 0.5, 2, 5]

# Different interpolations
interpolation = [cv2.INTER_NEAREST, cv2.INTER_LINEAR, cv2.INTER_AREA, cv2.INTER_CUBIC, cv2.INTER_LANCZOS4]

# Resize the image using different scaling ratios and interpolations
fig = plt.figure()
rows = len(scaling_ratio)
columns = len(interpolation)
count = 1
for i in range(rows):
    for j in range(columns):
        if count > rows*columns:
            break
        new_size = (int(w*scaling_ratio[i]), int(h*scaling_ratio[i]))
        count += 1
        resized_img = cv2.resize(img, new_size, interpolation[j])
        resized_img = cv2.cvtColor(resized_img, cv2.COLOR_BGR2RGB)
        fig.add_subplot(rows, columns, count).title(f"Scaling Ratio: {scaling_ratio[i]}, Interpolation: {interpolation[j]}")
        plt.imshow(resized_img)

plt.show()

# 导入所需库
import cv2
import matplotlib.pyplot as plt

# 读取输入图像
img = cv2.imread('birds.jpg')

# 使用不同的插值调整图像大小
resize_cubic = cv2.resize(img,(0, 0),fx=2, fy=2, interpolation = cv2.INTER_CUBIC)
resize_area = cv2.resize(img,(0, 0),fx=0.5, fy=0.7, interpolation = cv2.INTER_AREA)
resize_linear = cv2.resize(img,(0, 0),fx=2, fy=2, interpolation = cv2.INTER_LINEAR)

# 显示原始图像和调整大小后的图像
plt.subplot(221),plt.imshow(img), plt.title("原始图像")
plt.subplot(222), plt.imshow(resize_cubic), plt.title("插值Cubic")
plt.subplot(223), plt.imshow(resize_area), plt.title("插值Area")
plt.subplot(224), plt.imshow(resize_linear), plt.title("插值Linear")
plt.show()